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Salary: USD 320,000 - 405,000 / annual
Anthropic is seeking a Data Engineer to build the data foundation for the company's quote-to-cash lifecycle—the path a deal takes from opportunity through revenue. You will design canonical data models so that Sales, Deal Desk, Order Management, Revenue Operations, and Finance work from one governed, auditable definition of what was sold, on what terms, and where each deal stands.
Key responsibilities include:
- Translate data needs from Deal Desk, Order Management, Revenue Operations, Finance, and Sales systems teams into technical requirements
- Design, build, and own data models that transform raw Salesforce, CPQ, and billing data into canonical datasets
- Establish high data integrity standards and SLAs to ensure timely, accurate delivery
- Partner with Salesforce, CPQ, and billing engineers on upstream schema changes, new fields, and ingestion
- Build foundational data products, dashboards, and tools to enable self-serve analytics across GTM teams
- Influence stakeholder roadmaps from a data perspective and become the expert on Anthropic's GTM data models and architecture
You should have 5+ years of experience as a Data Engineer, Analytics Engineer, or similar role, ideally partnering with GTM, Revenue Operations, or Finance teams. Hands-on experience modeling Salesforce data and at least one adjacent quote-to-cash system (CPQ, contract lifecycle management, billing, or ERP) is essential. You'll need expertise in building multi-step ETL jobs, robust data models using dbt, workflow management with Airflow, and version control with GitHub. Strong SQL and Python skills are required, along with experience building data reporting and dashboarding in tools like Hex. A bias for action, full-stack mindset, and ability to thrive in ambiguity are critical. Experience building Analytics Data Engineering functions at startups is a plus.
